The paper investigates the effectiveness of various methods of organizational forgetting management (including counteracting accidental loss of necessary and supporting intentional unlearning of unnecessary knowledge) in Russian mechanical engineering companies. The methodology of the research is based on an econometric estimation of the influence of intensity of usage of several knowledge management practices on the organizational forgetting management effectiveness, applying regression analysis in the form of an ordered logit regression. The questions of the survey have been answered by respondents belonging to senior management of 81 companies. According to the results, a positive influence is exerted by intensity of regular analysis and documentation of critically important knowledge and knowledge gaps, control of quality of knowledge obtained from partners, and adaptation of the new knowledge to the existing; intensity of getting rid of knowledge having lost its actuality is negative. On the basis of the obtained results, recommendations are suggested considering the development of organizational forgetting management in Russian companies of mechanical engineering industry.
Original languageEnglish
Title of host publicationANNUAL GSOM EMERGING MARKETS CONFERENCE 2019
Subtitle of host publicationConference book
Place of PublicationSt. Petersburg
PublisherИздательство Санкт-Петербургского университета
Pages154-156
StatePublished - 2019
Event6th international GSOM Emerging Markets Conference-2019 - St. Petersburg State University, Graduate School of Management, Санкт-Петербург, Russian Federation
Duration: 3 Oct 20195 Oct 2019
Conference number: 5

Conference

Conference6th international GSOM Emerging Markets Conference-2019
Abbreviated titleGSOM EMC 2019
Country/TerritoryRussian Federation
CityСанкт-Петербург
Period3/10/195/10/19

    Research areas

  • KNOWLEDGE MANAGEMENT, KNOWLEDGE SHARING, ORGANIZATIONAL FORGETTING, ORGANIZATIONAL UNLEARRNING, MECHANICAL ENGINEERING

    Scopus subject areas

  • Management of Technology and Innovation

ID: 51177462